Recent studies, such as those on pancreatic cancer, indicate that microRNA (miRNA) are effective biomarkers for several types of cancer, with over 100 of them identified that act as oncogenes, tumor suppressors, and modulators of cancer stem cells and metastasis. MiRNA profiles have the potential to be highly effective in the early diagnosis of cancer at high specificity before clinical signs emerge. Current technology for miRNA sequencing, quantitative reverse transcribe-polymerase chain reaction (qRT-PCR), is difficult to multiplex and too expensive to be used for screening. The proposed research will develop a technology for quantitative miRNA profiling using microarrays that are considerably less expensive and easy to multiplex. Microarrays, however, have challenges: (a) the small size of miRNA makes the inference unreliable due to poor statistics caused by nonspecific binding; (b) the one to few nucleotide (nt) variation in the sequence from the same family of pre-miRNA is difficult to discern, (c) RT-PCR of small miRNAs used to make cDNA is not straightforward, and (d) PCR skews the distribution by exaggerating the amplification of miRNA sequences that are larger in relative concentration. The goal of the proposed R21 research is to develop a microarray method for profiling a miRNA sequence without PCR by measuring probe-target binding that is blind to nonspecific binding. The signal will quantitatively distinguish between perfect binding (PM), single nucleotide mismatch (1MM), and size heterogeneity. This proof-of-concept study will focus on synthetic and blood derived miRNA of the same sequence. A method, developed in Saraf's lab, can electrochemically read microarray spots on a monolith electrode by simply scanning a laser. Scanning Electrometer for Electrical Double-layer (SEED) can detect less than 1 atto-moles (amoles) of immobilized probe-target binding and differentiate between PM and 1MM; and nonspecific binding produces minimal signal. The 0.1aMole responsivity of SEED will be leveraged using an additional innovation to enhance binding efficiency to achieve a limit of detection (LOD) of at least 0.05 nM, requiring 0.2 ng miRNA. The study will be organized into three specific aims: 1) SEED performance will be quantified using synthetic miRNA, 2) mixtures of synthetic miRNA will be quantitatively analyzed, and 3) serum samples from pancreatic cancer patients and healthy controls will be analyzed using SEED. SEED is a potentially transformative technology that will leverage the rapidly growing knowledge base of miRNA biomarkers and a proven electrochemical transduction method for detecting specific binding without using labels at minimal background. The paradigm of the technology is that it addresses the background issue in microarrays at the hardware detection level rather than at the design-of-experiment level. If successful, the team will validate the method via an R33 using biospecimens for specific cancers to initiate translation to a screening technology and hypothesis-driven R01 research.